Observability is essential for the success of any application. However, definition of observability is tricky. Some people confuse them with surveillance or logging, and others think that this is actually about analysis, which is only a part of observability.
Observability, if you complete it correctly, you can make an incredible insight on the deep internal part of the system, and allow you to propose a complex problem -centered problem, such as:
- Where is your system fragile?
- What are you doing well?
- What should come next in your product roadmap?
- Does any code need to be reworked/rewritten?
- Where are your common points of failure?
All these are important questions to be asked. You can answer the data driving information created by good observability practices.
In this article, you will understand what is observability, why important and observability issues help solve. You will also understand some of the best practices that can be observability and how to implement it so that you can start to improve your application today.
What is observability?
Observability is what you understand what happened inside the software system without writing a new code.
If you are asked which microservices are encountering the most errors, then what is the worst part in the system, or the most common front -end errors you have encountered, can you answer these questions? If your team must go away and write code to answer them, it can be said that your system cannot be observed. This means that whenever new problems are raised, your system will continue to become a WHACK-A-MOLE game.
Why is observability important?
Good observability allows you to obtain data -driven positive business results. Know what to do, what to improve, and ignore what to promote your company from success to success, and save time for your customers, not even real problems, such as providing language in your aspect. Your customers are most likely not to use.
Observability is essential for new software practice. In the past few decades, the software system has become more and more complicated. However, surveillance the best practice has not been developed at the same speed. Traditionally, web development is performed using Lamp (Linux, Apache, MySQL, PHP/Perl/Python) stack. The stack is a large database with some middleware, web layer and a cache layer. The lamp pile is very simple, and the debugging is quite insignificant. All you have to do is to load all the above scale, and due to the nature of the application, you can quickly classify, fix and release any problems.
However, now, due to the cloud infrastructure, distributed microservices, various languages, multiple languages, multiple software products and container arrangement technology, software products, frameworks, examples and libraries have greatly improved the complexity of the system.
Observability can help you inquire and answer important questions about software systems and all different states that can pass through observation.
According to Stripe’s developer coefficient report, good observability can save 42 % of the company’s developer time, including debugging and reconstruction.
What problems does observability help solve?
When you follow a good observability practice and bake them directly into the software system, there are many benefits, including the following:
Releases are faster
When you understand the system more, you can iterate faster. You can save the days of developers to debug fuzzy random issues.
For example, I have millions of concurrent users in billions of dollars in work experience. One of the tasks of the entire software team is to view the logs that support queues and try to solve them. However, this is a very difficult task. All teams that the team once got were stack tracking and wrong logs. This enabled developers to browse the code for several hours, trying to track the most likely error reason.
In many cases, the reason (suspicion) is fixed and released by QA, but the developer is wrong, and the process must start again.
Incidents become easier to fix
When you have clear insights and data on the key parts of code and business, you will provide developers with the context and information required for repairing things.
The company can never repair what they cannot measure. This is also applicable to events.
With key information, such as the following content, you can significantly reduce the average time of recovery in the event:
- How do you replicate the incident?
- When does it happen?
- Is there a workaround?
- Does a service error occur when you replicate the incident?
Three pillars of Observability
Remember the three pillars of observability: logs, indicators and traces. These are different types of time series data, which can help improve the observability of the system. Using a time series database like InfluxDB, you can use these types of data more easily and use these types of data.
These are the useful and important components of the system’s observability. For example, a log is a time record of events in the system. The indicator is the number of data measured by the time -shifting measurement (that is, 100 customers use your website within an hour). The trace is the representative of the events related to the flow of your system (that is, the customer hit the landing page, add a T -shirt to the shopping cart, and then buy the shirt).
Each of these provides unique and powerful insights for your system and can help you improve it.
In this article, you understand the importance of observability and common problems that often occur when you encountering observability, such as why it is important and what problems it solves. You also understand the differences between observability and monitoring.
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